Instructions to use annakotarba/model_fine_tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annakotarba/model_fine_tuning with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="annakotarba/model_fine_tuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("annakotarba/model_fine_tuning") model = AutoModelForQuestionAnswering.from_pretrained("annakotarba/model_fine_tuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from annakotarba/model_fine_tuning: direct link, hf CLI and curl.
- Browser
- Download file 709 MB
-
https://huggingface.co/annakotarba/model_fine_tuning/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://annakotarba/model_fine_tuning/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/annakotarba/model_fine_tuning/resolve/main/pytorch_model.bin
709 MB
- Xet hash:
- 53a0f53dd50be64d6fb3330e9871a06a5122539d41778b10d606e9ff9c7b36db
- Size of remote file:
- 709 MB
- SHA256:
- fe3396d5a1fb2784871c552471e9c8212674d30bcd08c7266d33a34123f806b5
路
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